code: def _histogram_fixed_width_bins(
      values, value_range, nbins=100, dtype=np.int32, name=None
  ):
      """Numpy implementation of `tf.histogram_fixed_width_bins`."""
      del name
      nbins_float = np.array(nbins, values.dtype)
      scaled_values = truediv(
          values - value_range[0], value_range[1] - value_range[0]
      )
      indices = floor(nbins_float * scaled_values)
      indices = clip_by_value(indices, 0, nbins_float - 1).astype(
          utils.numpy_dtype(dtype)
      )
      return indices
  
file_path: probability/tensorflow_probability/python/internal/backend/numpy/misc.py
imports: import collections
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import errors
  from tensorflow_probability.python.internal.backend.numpy.numpy_math import floor
  from tensorflow_probability.python.internal.backend.numpy.numpy_math import truediv
  from tensorflow_probability.python.internal.backend.numpy.ops import _convert_to_tensor
  from tensorflow_probability.python.internal.backend.numpy.ops import clip_by_value
  from tensorflow_probability.python.internal.backend.numpy.ops import is_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: _histogram_fixed_width_bins(values, value_range, nbins, dtype, name) and returns: indices